Category: Uncategorized

Tesla unveiled its Master Plan Part 4, marking a dramatic pivot from its electric vehicle (EV) roots to a future centered on artificial intelligence (AI) and robotics. The plan, announced by CEO Elon Musk on X, emphasizes “sustainable abundance” through AI-driven technologies, particularly the Optimus humanoid robot and Full Self-Driving (FSD) systems. Unlike previous plans focused on EVs and sustainable energy, this 983-word document prioritizes AI integration into physical systems, aiming to redefine labor, mobility, and energy. Tesla projects that 80% of its future value will come from Optimus, with plans to produce 5,000 units in 2025 and 1 million annually by 2029, targeting industries like logistics and elder care.

The plan outlines five principles: unlimited growth, innovation to overcome constraints, solving real-world problems, autonomy for all, and widespread adoption driving growth. Optimus, now in its Gen 3 iteration with AI6 chips and vision-based training, is designed to handle monotonous or dangerous tasks, freeing humans for creative pursuits. Tesla’s FSD technology complements this, aiming to enhance transportation safety and accessibility. The company leverages its EV manufacturing expertise and AI infrastructure, including the Dojo supercomputer, to scale production, with a $16.5 billion Samsung partnership for AI5 chips bolstering its supply chain.

However, the plan has drawn sharp criticism for its vagueness. Commentators like Fred Lambert of Electrek call it a “smorgasbord of AI promises” lacking clear execution timelines, with some labeling it “utopic nonsense” designed to hype shareholders amid Tesla’s challenges. Tesla’s vehicle sales dropped 13% in the first half of 2025, with steep declines in Europe (47% in France, 84% in Sweden), and a 71% net income drop reflecting financial strain. Critics argue that Tesla’s focus on unproven robotics, with Optimus demos limited to tasks like serving popcorn, diverts resources from its core EV business, which faces rising competition from brands like BYD.

Skeptics also highlight technical hurdles, such as overheating in Optimus prototypes, and competition from firms like Unitree and Boston Dynamics. X posts echo mixed sentiment: some users praise the visionary shift, while others question its feasibility, citing past unfulfilled promises like full FSD deployment. Despite this, analysts project a $4.7 trillion humanoid robot market by 2050, suggesting Tesla’s pivot could yield significant long-term value if executed successfully. As Tesla navigates declining margins and regulatory scrutiny, its bold bet on AI and robotics positions it as a potential leader in a machine-driven future, but the path remains fraught with uncertainty.

Google has backtracked on its original plan to completely shut down all goo.gl shortened URLs by August 25, 2025. Instead of deactivating all links, Google will only disable those goo.gl URLs that showed no activity in late 2024. All other actively used goo.gl links will be maintained and continue to function normally. This reversal comes after Google received significant user feedback highlighting that many goo.gl links are still embedded and actively used across numerous documents, videos, posts, and more.

Originally, Google had stopped creating new goo.gl short links in 2019 and announced in mid-2024 that all goo.gl links would stop working completely on August 25, 2025, citing diminishing traffic with over 99% of links showing no recent activity. Beginning August 23, 2024, links with no activity started showing a warning message about their impending shutdown. Following reconsideration, Google confirmed it will preserve all goo.gl URLs that still have activity, meaning those links without the warning message will keep working beyond August 25, 2025.

To summarize:

• Inactive goo.gl URLs (no activity late 2024) will be deactivated as originally planned on August 25, 2025.
• Actively used goo.gl URLs will continue to operate normally.
• Warnings about deactivation are shown only on inactive links.
• Users are advised to check their links by clicking on them—if no warning appears, the link will remain functional.

This change reflects Google’s acknowledgment of the importance of these active links embedded widely across the web and is a partial reversal of their initial full shutdown plan.

Tesla is facing significant setbacks in its Optimus humanoid robot production. The company aimed to produce 5,000 Optimus units in 2025 but has only managed to build a few hundred so far. The main challenges causing delays include underdeveloped hand and forearm components, overheating joint motors, battery issues, and general hardware reliability problems. Many completed robot chassis are currently idle as Tesla engineers work to fix these technical issues.

Production was paused in mid-2025 following the departure of Milan Kovac, the original project leader, and the team is now undergoing a major redesign under new leadership led by Ashok Elluswamy. Tesla expects production of the updated “Optimus 3” model to start only in early 2026. CEO Elon Musk has moderated earlier ambitious timelines, acknowledging that the 2025 production target looks increasingly unachievable, though he remains optimistic about scaling production in the longer term, with a goal of one million units per year within five years.

These delays and leadership changes have drawn scrutiny and raised doubts about Tesla’s ability to meet short-term targets, though the company still sees the Optimus project as strategically important for the future.

Gemma 3n is Google’s latest mobile-first generative AI model designed for on-device use in everyday devices like smartphones, laptops, and tablets. It is engineered to deliver powerful, efficient, and privacy-focused AI capabilities without relying on cloud connectivity.

Why Gemma 3n is Popular?

• Mobile-First and On-Device Efficiency: Gemma 3n uses innovative technologies such as Per-Layer Embeddings (PLE) caching and the MatFormer architecture, which selectively activates model parameters to reduce compute and memory usage. This allows it to run large models with a memory footprint comparable to much smaller models, enabling AI tasks on devices with limited resources and without internet access.
• Multimodal Capabilities: It supports processing of text, images, audio, and video, enabling complex, real-time multimodal interactions like speech recognition, translation, image analysis, and integrated text-image understanding. This versatility makes it suitable for a wide range of applications, from virtual assistants to accessibility tools and real-time translations.
• High Performance and Speed: Gemma 3n is about 1.5 times faster than its predecessor (Gemma 3 4B) while maintaining superior output quality. It also features KV Cache Sharing, which doubles the speed of processing long prompts, making it highly responsive for real-time applications.
• Privacy and Offline Use: By running AI models locally on devices, Gemma 3n ensures user data privacy and reduces dependence on cloud servers. This offline capability is especially valuable for users and developers concerned about data security and latency.
• Wide Language Support: It supports over 140 languages with improved performance in languages such as Japanese, German, Korean, Spanish, and French, helping developers build globally accessible applications.
• Developer-Friendly: Google offers open weights and licensing for responsible commercial use, allowing developers to customize and deploy Gemma 3n in their own projects, fostering innovation in mobile AI applications.

As a summary, Gemma 3n is popular because it brings powerful, multimodal AI capabilities directly to mobile and edge devices with high efficiency, speed, and privacy. Its ability to handle diverse inputs (text, images, audio, video) offline, combined with strong multilingual support and developer accessibility, positions it as a breakthrough for next-generation intelligent mobile applications